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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Seminar Nasional Teknologi Informasi Komunikasi dan Industri JURNAL INSTEK (Informatika Sains dan Teknologi) KOMPUTIKA - Jurnal Sistem Komputer TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research
Fitri Insani
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences

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UPAYA INDONESIA MEMBEBASKAN TENAGA KERJA INDONESIA TERPIDANA HUKUMAN MATI DI ARAB SAUDI (2011-2013) Fitri Insani; Ahmad Jamaan
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Vol 2, No 1: WISUDA FEBRUARI 2015
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Riau

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Abstract

This research describes about effort of Indonesia to acquitted Indonesia labours who get death penalty in Saudi Arabia’s (2011-2013). There are some Indonesian labours that have been accused of committing a crime that drags them become a convict of the death penalty by a court of Saudi Arabia’s. There are three kind of the death penalty in Saudi Arabia’s, they are: Qishas, Rajam and Ta’zir. As for the allegations imposed on Indonesian labours that under sentence of death in Saudi Arabia’s are torture, murder, perform of magic and adultery.This research used the theory of diplomacy. As for the kind of diplomacy that used are bilateral diplomacy. Bilateral diplomacy is diplomacy carried out by between two countries. This research used nation-state analysis.This study applies qualitative research method with library. The data sources are from books, journal, and the internet.Finnaly, Indonesian government’s actions in providing protection for Indonesian labours who became convicted of the death penalty in 2011-2013 is considered to be the maximum. As for the efforts that has been made are: do moratorium policy, bilateral diplomacy, forming a special task force, appoint of retainer lawyer and assist in paying (diyat) to the families of victims. Those efforts can help the Indonesian labours who convicted of death penalty and get a lighter punishment like a forgiveness from the victim’s family or pay a fine.Keywords: Bilateral Diplomacy, Death Penalty, Effort, Indonesian Labours
Penerapan Genetic Modified k-Nearest Neighbor Pada Prediksi PM10 di Pekanbaru Fitri Insani; Syarifatun Nissa
Komputika : Jurnal Sistem Komputer Vol 10 No 2 (2021): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v10i2.4404

Abstract

Penerapan metode algoritma genetika dan modified k-nearest neighbor(MKNN) dengan deret waktu telah digunakan dalam penelitian ini. Metode MKNN dan algoritma genetika digunakan untuk memprediksi particulate matter (PM10) di kota Pekanbaru. Data PM10 yang digunakan merupakan data PM10 per 30 menit pada bulan Juli sampai bulan Desember tahun 2015 yang diambil dari laboratorium udara kota Pekanbaru. Data ini kemudian diubah menjadi deret waktu dengan 48 variabel masukan dan 1 variabel keluaran. Hasil dari penelitan ini menunjukkan bahwa metode MKNN dapat memprediksi PM10 dengan error terendah yaitu 8,957 dan metode algoritma genetika dapat mencari nilai k optimal pada MKNN dengan k optimal yaitu 3.
Analisa Perbandingan Metode Dempster-Shafer (DS) Dan Certainty Factor (CF) Dalam Mendiagnosa Hama Dan Penyakit Kacang Tanah Okfalisa Okfalisa; Yelfi Vitriani; M Fadhli Ihsan; Fitri Insani; Novi Yanti; Frica A Ambarwati; Eggy P
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2018: SNTIKI 10
Publisher : UIN Sultan Syarif Kasim Riau

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Beberapa masalah meningkat untuk meningkatkan diagnosa hama dan penyakit pada kacang tanah. Adanya kendala yang dihadapi pada buruknya kesuburan tanah, penyakit, jamur, virus, dan hama dapat memicu mengurangi produktivitas tanaman, kualitas dan nilai. Terlebih, beberapa sumber langka dari varietas unggul, serta pengetahuan dari petani yang terbatas pada produksi benih, panen dan pengolahan tanaman itu sendiri. Makalah ini mengkaji penerapan metode Dempster-Shafer (DS) dan metode Certainty Factor (CF) untuk akurasi data yang tepat dalam mencari solusi yang diharapkan dengan menganalisa perbandingan metode tersebut. Analisis mengikuti proses dari sistem pakar termasuk pengolahan gejala-gejala, cara pengendalian, nilai probabilitas untuk DS dan CF, Rulebase Reasoning serta hasil diagnosa sistem dan pakar. Untuk menguji validitas dan keakuratan data kedua metode dengan Confusion Matrix, statistika deskriptif, Uji Mann Whitney dan uji T Independent Sample. Sebagai hasilnya, ada 13 hama/penyakit dari 13 terdapat perbedaan nilai kepercayaan antara kedua metode. Rata rata perbedaan dari 13 data uji adalah 16,48%. Terlihat pada metode CF nilai kepercayaan lebih tinggi daripada metode DS. Pengujian ini juga mencari solusi yang diharapkan berdasarkan keakuratan data dari metode yang tepat berdaskan uji T Independent Sample. Dari hasil perhitungan hasil uji T Independent Sample pada asumsi data terdistribusi normal dijelaskan bahwa didapatkan hasil bahwa probabilitas kesalahan (0,000), sedangkan pada kriteria pengujian dengan tingkat signifikansi α 0,05 (keyakinan 95%). Ini menunjukkan bahwa Hipotesis ditolak, maka dapat disimpulkan bahwa metode DS lebih tepat untuk diterapkan pada sistem pakar diagnosa hama dan penyakit pada kacang tanah.
Aplikasi Prediksi Respon Displacement dan Story Drift Bangunan terhadap Spektrum Gempa dengan Metode Backprepogation Okfalisa saktioto; Eggy P; Yelvi Fitriani; Fitri Insani; Novi Yanti; Frica A Ambarwati
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2018: SNTIKI 10
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Gempa bumi merupakan kejadian unik yang  tidak bisa ditentukan, baik waktu kejadian, lamanya waktu berlangsung (durasi) maupun kekuatan. Untuk memprediksi terjadinya gempa tidaklah mudah, maka salah satu cara yang dapat dilakukan adalah bagaimana mengatasi atau  memperkecil pengaruh kerusakan yang ditimbulkan  akibat gempa tersebut. Beban gempa menjadi aspek penting yang perlu diperhitungkan dalam mendesain bangunan sebuah gedung. Respon bangunan yang tidak aman akan menyebabkan kerusakan bangunan yang selanjutnya mengarah kepada kerugian, baik secara fisik maupun finansial. Guna mencegah terjadinya kecelakaan dan meminimalisir resiko dalam pembangunan, maka penelitian ini memprediksi nilai respon suatu bangunan melalui penerapan konsep Jaringan Syarat Tiruan Backpropagation Neural Network (BPNN). Prediksi dilakukan pada tipe bangunan displacement dan story drift berupa nilai respon dengan parameter  mutu beton, percepatan tanah puncak (PGA), percepatan spectrum desain (SDS), parameter SD1, waktu sebelum getaran (T0), dan waktu setelah getaran (Ts). Untuk simulasi pengujian digunakan 330 data dari 10 provinsi yang ada di Indonesia. Parameter BPNN yang digunakan yaitu nilai epoch 500, nilai learning rate 0.01-0.09 , arsitektur 6 neuron input layer, 6 neuron hidden layer dan 1 output. Simulasi perbandingan jumlah data latih dan data uji yang digunakan adalah 90:10, 80:20, 70:30; dan 50:50. Berdasarkan hasil pengujian, diperoleh nilai akurasi tertinggi pada displacement=93,0446% dan story drift=  94,6599%  untuk simulasi 90:10 dan learning rate 0.09. Hasil ini menunjukkan bahwa metode BPNN telah berhasil diterapkan untuk memprediksi respon bangunan terhadap gempa dengan tingkat akurasi yang cukup baik. 
IMPLEMENTASI ALGORITMA FOLD-GROWTH UNTUK MENEMUKAN POLA KELULUSAN MAHASISWA Muhammad Hasbi Assidiqqi; Alwis Nazir; Iwan Iskandar; Jasril Jasril; Fitri Insani
TEKTRIKA Vol 7 No 2 (2022): TEKTRIKA Vol.7 No.2 2022
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v7i2.5530

Abstract

Timely graduation of students is important for a study program and higher education institution. According to BAN-PT Regulation Number 23 of 2022 concerning Instruments for Monitoring and Evaluation of Higher Education Accreditation Ratings, the ideal percentage of student graduation on time is ? 37.5% for academic tertiary institutions and ? 47.5% for vocational tertiary institutions. The timely graduation of Informatics Engineering Study Program students at UIN Sultan Syarif Kasim Riau every year is still below the standards set by BAN-PT. In 2021 the number of students who graduate on time is only 12%. By using student data in the form of acceptance and graduation data in the form of length of study and GPA, excavation of graduation patterns is carried out using the FOLD-Growth algorithm. The FOLD-Growth algorithm is a combined algorithm of FOLDARM and FP-Growth. With 274 student data, a minimum support value of 20%, and a minimum confidence of 50%, it produces two patterns with the strongest lift ratio value of 3.61, while with a minimum support of 10% and a minimum confidence of 50%, it produces three patterns. with the strongest lift ratio of 7.03. The results of this study can be used as a guideline for increasing student graduation rates on time, by providing a larger intake quota for new students on a pathway that results in on-time graduation, so that it will increase student graduation on time. Key Words: Student graduation, Association Rule, lift ratio, FOLD-Growth, FP-Growth
Pencarian adverse event yang timbul akibat penggunaan obat dexamethasone menggunakan algoritma apriori Nuradha Liza Utami; Alwis Nazir; Pizaini; Elvia Budianita; Fitri Insani
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

Inflammation is the body's response to infection, irritation, or injury characterized by redness, increased temperature, swelling, and pain. Dexamethasone is one of the drugs from the corticosteroid group that is commonly used, dexamethasone has a wide indication in medicine is often considered a drug that can save lives, causing many people to then buy dexamethasone drugs without medical indications and prescriptions assuming dexamethasone drugs can treat various diseases. The use of dexamethasone can result in side effects including decreased immunity, diabetes, hypertension, moon face, osteoporosis, and cataracts. In addition to frequent side effects, adverse events may also occur. This study aims to find the relationship of adverse events that arise as a result of using dexamethasone drugs, by applying the data mining technique of association rule method with apriori algorithm. The dataset used in the research is sourced from the FDA Adverse event Reporting System (FAERS) database which is managed using the KDD stages which include data selection, cleaning, transformation, and data mining. the results of the research are implemented into the apriori algorithm data mining system and tested using the lift ratio value. The rules generated in this study have a lift ratio value of more than 1, which means that the rules generated are valid and show the benefits of these rules.
Model Prediksi Jumlah Penjualan Pelumas Mesin Di PT. X Dengan Algoritma Naïve Bayes Purnama, Nilam; Fitri Insani; Elin Haerani; Iis Afrianty
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.8250

Abstract

Machine lubricants are essential materials used to reduce friction between two moving surfaces, improve machine efficiency, and extend the lifespan of components. This study aims to predict the sales volume of machine lubricants at PT. X using the Naïve Bayes algorithm. The data used includes attributes such as year, month, material description, total allocation, realization, and remaining allocation, with a total of 3,006 data points obtained from PT. X's Warehouse Management System (WMS). The model was tested using the 10-Fold Cross Validation method and testsing without such validation. The test results show an accuracy of 71% with 10-Fold Cross Validation, compared to 14% without validation. Additional testing showed an accuracy of 5%, with RMSE of 124.71 and MAPE of 0.95. Based on these results, it is recommended to optimize data preprocessing, such as handling data imbalance and feature normalization, to improve prediction accuracy. Furthermore, using more diverse validation techniques, such as stratified cross-validation, can provide more stable evaluations. Given that predictions are influenced solely by historical data, it is recommended to periodically update the data to keep the model relevant and accurate. This research is expected to assist PT. X in planning sales strategies and managing lubricant stock more effectively.
Implementasi Algoritma Improve Apriori Terhadap Keluarga Beresiko Stunting Muhammad Habib Nazlis; Fitri Insani; Alwis Nazir; Iis Afrianty
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

Stunting is a serious health issue in Indonesia, particularly among families with low socio-economic conditions. However, the lack of precise criteria or measurements of social conditions contributing to at-risk families makes prediction challenging. This study aims to identify patterns of relationships among 17 criteria influencing stunting risk, such as maternal age, number of children, type of flooring in the house, and access to clean water, by enhancing the efficiency of the Apriori algorithm through hash-based techniques. Data were obtained from families in Tuah Madani District, Pekanbaru, and analyzed using data preprocessing and transformation methods. The implementation of this algorithm within a web-based information system enables rapid and efficient analysis to identify stunting risks based on relevant combinations of criteria. The analysis results indicate that certain criteria, such as maternal age above 35 years, status as a couple of childbearing age (PUS), and having more than three children, are significantly associated with stunting risk, with a support value of 37.54% and a confidence level of 83.16%. This study contributes to the development of efficient methods for stunting risk analysis and provides a foundation for more targeted health interventions. Future researchers are advised to expand the data scope by including additional regions and different time periods to improve result generalization. Furthermore, incorporating other variables, such as maternal nutritional status or the education level of household heads, may offer deeper insights into understanding stunting risk patterns.
Analisis Perbandingan Metode DBSCAN dan Meanshift dalam Klasterisasi Data Gempa Bumi di Indonesia MHD Ade Setiawan; Fitri Insani; Yelfi Vitriani; Yusra
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.605

Abstract

Indonesia is one of the countries with a high vulnerability to earthquakes due to its location at the convergence of three major tectonic plates: the Indo-Australian, Eurasian, and Pacific plates. As a result of this interaction, seismic activity is highly frequent across various regions. Understanding the distribution patterns of earthquakes is essential for disaster risk mitigation. One approach used to analyze these patterns is clustering, particularly using the DBSCAN  and Meanshift algorithms, which can group spatial data without predefining the number of clusters. This study aims to compare the effectiveness of both algorithms in clustering earthquake data based on spatial parameters, namely latitude and longitude. Evaluation was conducted using cluster visualization and the Silhouette Score as the clustering validity metric. The results show that DBSCAN  produces more optimal clustering with a Silhouette Score of 0.930028, higher than Meanshift's score of 0.90103. DBSCAN  is also capable of detecting relevant outliers in earthquake analysis, while Meanshift generates more clusters but with less separation. Using spatial parameters such as latitude and longitude, DBSCAN  is considered more effective in identifying the spatial distribution patterns of seismic activity in Indonesia based on earthquake data. This research supports the development of decision support systems for earthquake disaster mitigation and serves as a reference for selecting appropriate clustering methods for spatial data analysis.
Pengelompokan Wilayah Bencana Banjir di Indonesia Menggunakan Algoritma K-Means Wenny Tarisa Oktaviany; Fitri Insani; Alwis Nazir; Pizaini
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.608

Abstract

Floods are one of the natural disasters that often occur in Indonesia, especially during the rainy season. This disaster is caused by various factors, both natural and caused by human activities, such as high rainfall, poor drainage systems, land conversion, and suboptimal spatial planning. The impact of floods is very detrimental, both physically and psychologically, including loss of life and damage to property. Therefore, a method is needed to group areas based on their level of vulnerability to flooding. This study aims to group flood disaster areas in Indonesia using the K-Means algorithm. The data used comes from the BNPB Geoportal covering flood events from January 2020 to December 2024, with a total of 7,487 events from 498 areas. Based on the test results obtained using the Silhouette Coefficient, it shows that 2 clusters were selected as the best number of clusters with a Silhouette Coefficient value of 0.8461 which is included in the strong clustering structure. Of the 2 clusters obtained, cluster 1 is a high-risk category consisting of 35 areas, while cluster 2 is a low-risk category consisting of 463 areas. The results of this study can provide information for related parties to improve the efficiency of flood disaster management.
Co-Authors Alwis Nazir Damayanti, Elok Eggy P Elin Haerani Elvia Budianita Frica A Ambarwati Iis Afrianty Iwan Iskandar Jasril Jasril M Fadhli Ihsan MHD Ade Setiawan Muhammad Habib Nazlis Muhammad Hasbi Assidiqqi Novi Yanti Nuradha Liza Utami Okfalisa Okfalisa Okfalisa saktioto Pizaini Pizaini Purnama, Nilam Rahmad Abdillah SURYA ADITYA GD Suwanto Sanjaya Syarifatun Nissa Wenny Tarisa Oktaviany Yelfi Vitriani Yelvi Fitriani Yusra